Development of a Simple Diagnostic Tool for Detecting Localized Roughness Features

Chatti, Karim; Zaabar, Imen; Lee, Hyung Suk

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Development of a Simple Diagnostic Tool for Detecting Localized Roughness Features

2009-02-01
By Chatti, Karim ; Zaabar, Imen ; Lee, Hyung Suk

File Language:

English

Details

Creators:

Chatti, Karim ; Zaabar, Imen ; Lee, Hyung Suk
Corporate Creators:

Michigan State University. Pavement Research Center of Excellence
Corporate Contributors:

Michigan. Dept. of Transportation. Construction and Technology Division
Subject/TRT Terms:
Publication/ Report Number:

RC-1505
Resource Type:

Tech Report
Geographical Coverage:

Michigan ; United States
Edition:

Final Report
Corporate Publisher:

Michigan. Dept. of Transportation. Construction and Technology Division
Abstract:

The collection of distress data from video imaging of the pavement surface can provide the location and type of many distresses. However, it cannot provide useful information about some distress features such as the magnitude of faulting, breaks and curling in concrete pavements. This report describes a simple tool to extract such information through the use of the raw profile data. Different methods were used in the study, including wavelets, time frequency and discrete methods. The discrete elevation difference method (DED) was selected for faulting and breaks detection, and the discrete slope method (DS) was selected for curling detection. To test the validity of the analysis, surveys were conducted on different sites in Michigan. The new tool was able to detect the magnitude of faulting, breaks and curling with an R2 of 0.97 and standard error (SE) of 0.25 mm. The localization was also highly accurate (R2 =0.99). The results indicate that the methods described above can capture relevant information about these roughness features with reasonable accuracy.
Format:

PDF
Download URL:

https://rosap.ntl.bts.gov/view/dot/40328/dot_40328_DS1.pdf
File Type:

[PDF - 3.20 MB]
Collection(s):

US Transportation Collection
Main Document Checksum:

urn:sha256:4038ece2abdc5d1c562ec422366f9af262c1146ab4de8aebac3186eb29e05a1f

File Language:

English

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